class_docstr: A baseline approach for computing the attribution. It multiplies input with
  the gradient with respect to input.
  https://arxiv.org/abs/1605.01713
code: def multiplies_by_inputs(self):
      return True
  
file_path: captum/captum/attr/_core/input_x_gradient.py
imports: from typing import Any, Callable
  from captum._utils.common import _format_output, _format_tensor_into_tuples, _is_tuple
  from captum._utils.gradient import apply_gradient_requirements, undo_gradient_requirements
  from captum._utils.typing import TargetType, TensorOrTupleOfTensorsGeneric
  from captum.attr._utils.attribution import GradientAttribution
  from captum.log import log_usage
label_desc: Use image node_id 3 for calling the InputXGradient obj's underlying member method code with example usage: obj.multiplies_by_inputs() and returns: True